Hzfengsy commented on a change in pull request #7831:
URL: https://github.com/apache/tvm/pull/7831#discussion_r612150174
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File path: python/tvm/topi/cuda/conv2d_hwnc_tensorcore.py
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@@ -254,13 +253,8 @@ def schedule_hwnc_tensorcore_cuda(cfg, s, Conv):
vector_as = cfg["vector_as"].val
vector_ws = cfg["vector_ws"].val
split_block_k_nums = cfg["split_block_k_nums"].val
- fuse_pack = cfg["fuse_pack"].val
- if not fuse_pack:
- s[packed_data].compute_inline()
- else:
- with Target("cuda"):
- schedule_injective_from_existing(s, packed_data)
+ s[packed_data].compute_inline()
Review comment:
Does it only happen in `int4` or it is a common problem for both
`int8/int4`?
If it is just for `int4`, we should not change it because it may make
`int8/float16` slower. alternatively, we can add a single file only for `int4`
schedule.
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